ces lecture 2 nigar hashimzade · 2019-12-30 · growth with public policies in r&d ces lecture...

Growth with public policies in R&DCES Lecture 2

Nigar Hashimzade

Durham and IFS

24/11/2016

NH (Durham and IFS) R&D policies 24/11/2016 1 / 39

Motivation and outline

Europe 2020 targets include 3% of EU GDP to be dedicated to R&Dinvestment(2/3 by private funding)

Underlying idea: public-good nature of R&D undermines privateincentives

Hence, government intervention: institutional arrangements (patentprotection); direct (subsidies) and indirect (tax credits) �nancialincentives to R&D in private sector;

Questions to consider:I Importance of R&D for economic growthI Importance of public policies for private R&D(especially with post-crisis budget squeeze)


Endogenous technological innovation

The Solow model shows that long-run growth is not possible withouttechnological progress

I Reason: decreasing returns

The model does not say where the technological progress comes from

Predictions are not always supported by empirical evidence:I Not all countries with low capital stock grow faster than countries withhigh capital stock

I Capital is not always �owing from rich to poor countries

In the models with human capital (Lecture 1) the engine of growth ishuman capital accumulation.

Alternative explanation: endogenous technological change(Romer, 1990; Jones, 1995; Aghion and Howitt, 1992)


Romer (1990)Romer (JPE 1990) is a version of a neo-classical growth model where theproduction function exhibits constant private returns but increasing socialreturns because of the knowledge spill-overs.

Three production sectors: research, intermediate goods, �nal good(plus consumers)

Physical inputs (labour, capital) are rival and excludable

New knowledge, or technology, is non-rival and (at least) partlyexcludable

I Once developed by one �rm can be used by any number of other �rms(non-rival)

I Other �rms have to buy the �blueprint�and so the inventor extracts amonopoly rent (excludable)

Development of new technology isI a horizontal innovation (new inputs)I a deliberate, rational choice


Romer (1990)Research sector: perfectly competitive; new knowledge productionfunction: .

A = δHAA

HA = human capital used in the research sector; A = existing stockof knowledge (technologies, designs, or �blueprints�)

I Linearity in A makes unbound growth possible.

Intermediate inputs sector: a continuum of �rms, each producing adistinct type of �machine�; �nal good is the only input,

x (i) = ηY .

To produce a new machine an intermediate �rm needs to buy a�blueprint�(patent) from the research sector.Final good sectors: perfectly competitive; CRS; a representative �rmuses a combinantion of existing intermediate inputs (imperfectsubstitutes), human capital, and unskilled labour,

Y = LαHβY

Z A

0x (i)1�α�β di


ProducersPro�t maximization assumptions:

Final good sector: choose fL,HY , fx (i)gg to maximize

πY = Y �Z A

0p (i) x (i) di � wLL� wHHY

Intermediate inputs sector: choose p (i) to maximize

π (i) = p (i) x (i)� rηx (i)I There is a �xed cost of buying a blueprint, or a patent , PA, prior toproduction

I Price of a blueprint equals present discounted value of the futurestream of pro�t

PA (t) =Z ∞

texp

��Z τ

tr (s) ds

�π (i ; τ) dτ

I Note: along the BGP PA =π(i )r .

Research sector: choose HA to maximize

πA = PA.A� wHHA


ConsumersUtility maximization assumptions:

U =Z ∞

0exp (�ρt)

c (t)1�σ � 11� σ

dt

A representative consumer chooses consumption and savings path

Consumers are endowed with unskilled labour and human capital, andown all �rms

Labour income is derived from unskilled labour, wLL and humancapital, wHH

I Supply of human capital is �xed, H = HA +HYI Supply of unskilled labout is �xed at L

Dividend income is derived from pro�ts of the intermediate input �rmsI Research and �nal good sectors earn zero pro�t and can be ignored inthe budget constraint.


EquilibriumStandard de�nition of the equilibrium (optimization; market clearing; plusmarket entry choice)Main features:

Knowledge enters into production in two distinct ways:I A new design enables production of a new input into �nal goodI A new design also increases the existing stock of knowledge

F Hence, it increases the productivity of human capital in the researchsector

In the BGP equilibrium stock of knowledge grows at a constant,endogenously determined rate

I Output and consumption grow at the same rateI Growth rate is negatively related to the rate of return on investmentwhich is endogenously determined by the consumer time preferences:

g =δH �Λρ

σΛ+ 1where Λ =

α

(α+ β) (1� α� β)


Johnson (1995)In the original formulation the rate of growth is proportional to thesize of R&D labour force (scale e¤ect), contrary to the empiricalevidence.Johnson (1995) suggested using share of labour force in the R&Dsector:

.A = δsAA where sA =

HAH.

Other modi�cations: decreasing returns to the stock of ideas;duplication/overlap in research or use of less skilled researchers:.A = δHAA

φhλ�1A where λ 2 (0, 1) and hA = HA in the BGP equilibrium.

I With φ 2 (0, 1) no long-run growth e¤ect, �only the level e¤ect onwelfare.

The role of R&D subsidies or tax credits:I Positive in Romer (1990)I Zero in Johnson (1995)


Schumpeterian growth: creative destruction

Alternative paradigm: Schumpeterian model, or growth throughcreative desctruction

Vertical innovationI Increase in quality;I Replacement of existing inputs;

Scale e¤ectI Growth rate is higher in larger economiesI In particular, economic integration leads to higher growth rate

A role for government policiesI Direct subsidies to R&D;I R&D tax incentives;I Competition regulations (patents; barriers to entry; exit costs; opennessto trade).


Schumpeterian growth: creative destruction

Economic growth is a social process.Three main features:

1 Innovations drive long-run growth2 Innovations result from entrepreneurial activities

1 Entrepreneurs invest in innovations2 They respond to economics incentives3 Incentives come from economic policies and institutions

3 Innovations replace old technologies

1 Creative desctruction2 Incumbents oppose the new competitors


Aghion-Howitt framework

In the original model (Aghion and Howitt, 1992) potential entrantsinnovate and displace incumbent �rms

I Competition reduces pro�t to be earned once in the marketI This implies negative correlation between competition and innovationI Empirically, positive correlation (Blundell et al., 1995)

Modi�ed framework (Aghion et al., 1997, 2001)I Incumbents innovate in order to stay in the marketI Two types of incumbent �rms: leaders and laggardsI Innovations are step-by-stepI U-shape relationship between competition and innovation(Aghion et al. 2005)


Aghion-Howitt frameworkSimple version (�partial equilibium�)

One �nal (numeraire) good produced competitively from imperfectlysubstitutable inputs:

yt =1α

Z 1

0[At (v)]

1�α [xt (v)]α , α 2 (0, 1) .

Final good can be used for consumption, production of intermediategoods, and investment in innovation.

Optimal choice of inputs gives the inverse demand for type-v input:

pt (v) =�At (v)xt (v)

�1�α

.

Inputs are produced by monopolistically-competitive �rms:

πt (v) =�pt (v)�

1ϕ

�xt (v)


Aggregate output and technologyOptimal level of production and equilibrium price:

xt (v) = [αϕ]1/(1�α) At (v) ; pt (v) =1

αϕ.

Equilibrium pro�t (surplus):

eπt (v) = (1� α) [αϕ]α/(1�α) At (v)

Aggregate output:

yt = α(2α�1)/(1�α)ϕα/(1�α)At ; At =Z 1

0At (v)

Productivity frontier is growing at a constant exogenous rate, g :

At = At�1 (1+ g)

At the end of period t � 1 a �rm can be in one of two states, H (atthe frontier, At�1 (v) = At�1) or L (one step behind the frontier,At�1 (v) = At�2)


Innovation decision

Before choosing the production plan a �rm can invest in an innovationI The outcome is stochasticI If successful (w/p z) productivity increases by a factor of (1+ g)I If unsuccessful (w/p 1� z) productivity remains the sameI In peroid t successful �rms who were H-type at t � 1 start as H-type,and all other �rms start as L-type

Cost of investment: C (z ,At�1 (v)) = 12 z2At�1 (v) .


New entrants

A new entrant can replace incumbent producer of good v w/prob h

Entry is pro�table only if the entrant can produce at the frontierI For H-type incumbent h = 0I For L-type incumbent h 2 (0, 1)

Probability of new entrant replacing incumbent �rm is exogenous butcan be linked to the institutional variables

I Higher h means lower barriers to entryI An increase in h means, e.g., liberalization of the economy, etc.


Optimal investment in innovation

An incumbent �rm is allowed to keep fraction β of produced surplus(e.g., after taxes etc.):

πt (v) = βeπt (v) = β (1� α) [αϕ]α/(1�α) At (v) � δAt (v)

At the end of period t � 1 incumbent �rms of both types chooseinvestment in innovation,

zH ,L = argmaxE [πt (v)� C (z ,At�1 (v))]

Expected net pro�ts:

πH = δ�zAt + (1� z) (1� h)At�1

�� 12cz2At�1

πL = δ�z (1� h)At�1 + (1� z) (1� h)At�2

�� 12cz2At�2


Equilibrium and comparative staticsThe interior solution (both types invest in innovation) is

zH =δ (g + h)

c; zL =

δg (1� h)c

The more advanced �rms invest more in innovation than the lessadvanced �rms: zH > zL

Higher competition makes more advanced �rms invest more, and lessadvanced �rms invest less in innovation: dz

H

dh > 0,dzLdh < 0

I The e¤ect of higher competition on aggregate investment can benon-monotone (in particular, can exhibit U-shape)

Both types invest more in innovation, the higher is the growth in theproductivity frontier (g), the lower the marginal cost of investment(c), and the higher the pro�tability (δ)

I In particular, an increase in pro�t tax reduces innovation investment forboth types.

More complicated models: two R&D sectors, variety and quality, plushuman capital accumulation (e.g., Young, 1998).


Government policies

The government can facilitate economic growth through innovationdirectly or indirectly

Direct innnovation incentives:I Subsidies or tax credits for R&DI Subsidies for training costsI Investment in human capitalI Patent protection

Indirect innovation incentives:I Competition policiesI Regulations

Theoretical and empirical support of incentive e¤ectiveness is mixed.


General equilibrium e¤ects

Schumpeterian growth model predicts that innovation-led growth can beeither excessive or insu¢ cient, depending on which e¤ect dominates:creative destruction or inter-temporal spill-over of knowledge.

Important: if social returns of a private activity are higher thanprivate returns the free-market provision of the activity is insu¢ cient.

Need to estimate correctly private and social returns to R&D

Jones and Williams (1998): links an endogenous growth model withspill-over e¤fects to the empirical estimates of the coe¢ cients; hence,helps interpret correctly the estimates of the social returns to R&D (lowerbound).


Empirical evidence

Gri¢ th (2000): social returns from R&D exceed private returns toinnovating �rms. Hence, government policies can improve e¢ ciency byincentivizing innovation.

Tax credits for R&D are e¤ective. However:I TC may reallocate R&D across countries without increasing the totalamount

I Create undesirable tax competition

Subsidies are e¤ective. However:I Distort other economic activitiesI May lead to higher wages of R&D scientists without increasing thestock of knowledge


Rate of return to R&D

Private rate of return can be estimated from the production function:

Yit = AitF (Kit , Lit )

lnAit = η lnGit + β lnXit

Stock of knowledge (Git) can be proxied by R&D expenditure.I Griliches (1992; panel of US �rms): η = 0.07; ratio of R&D stock tovalue added = 0.26; hence r = 0.07/0.26 = 0.27

Social rate of return can be estimated as the e¤ect of growth in a�rm from R&D in other �rms.

I Estimation can be done at a �rm level, industry level, or country levelI This will measure spill-over e¤ect, respectively, for a �rm, within anindustry, or within a country


Estimates of the social rate of returnGri¢ th (2000) gives a summary of several studies.

(these estimates are lower bounds, according to Jones and Williams, 1998)More recent studies: Monmartin and Massarde (2012); Westmore (2013).NH (Durham and IFS) R&D policies 24/11/2016 23 / 39

Monmartin and Massarde (JoES, 2012)Private R&D �nancing in the EU grows much slower than publicspending on R&DEmpirical methods of measuring social returns to R&D are weakThere is no strong evidence of underinvestment in R&D by privatesectorKnowledge externality is not the only market failure in R&D activitiesThe individual and aggregate e¤ect of di¤erent market failures maybe ambiguous:

Market failure Externality OutcomeSurplus appropriability + under-investDuplication � over-investRent transfer � over-investKnowledge: non-rival/congestion +/� ?Proximity: concentration +/� ?

Table: Market failures and private investment in innovation


Geography

Martin & Ottaviano (1999); other NEG/Growth synthesisThis strand of literature o¤ers analysis of R&D policies inglobalization/asymmetry context.

Knowledge spillovers are partially localized

Support for R&D a¤ects geographic distribution of economic activities

According to the NEGG, location choices by �rms have oppositee¤ects on the global transaction costs (lower with lowerconcentration) and the wealth of knowledge owner (lower with higherconcentration):

I Marginal cost of R&D investment can be above or below optimal level;I Firms will tend to under- or over-invest in R&D.


Westmore (OECD 2013)

Panel study of 19 OECD countries; private innovation activities (numberof patents; R&D expenditure).Main �ndings:

R&D tax incentives, direct government support, and patent rightshave positive e¤ect on innovation activities associated withproductivity growth;

I Weaker e¤ect of tax incentives where policies were changing frequently:predictable environment might be important;

I Stronger e¤ect of direct �nancial support in later years: policy designmight have improved;

I Stronger e¤ect of patent rights when regulatory barriers to entry arelow;

However, direct evidence of positive e¤ect of these policies onproductivity growth is weak.



Main �ndings:

Policies related to product market regulation, openness to trade, anddebtor protection in bankruptcy provisions are important for di¤usionof new technologies;

I Better access to foreign R&D is associated with less domestic R&D:substitutability;

I Convergence is faster with more openness to trade;I Convergence is faster with lower exit cost.



Data sample:

Years 1983�2008 in two models, 2986�2008 in one model

Country-level annual data on 19 OECD countries(Australia, Austria, Belgium, Canada, Denmark, Finland, France,Germany, Ireland, Italy, Japan, Netherlands, Norway, Portugal,Sweden, Switzerland, UK, USA).

Variables of interest:

(i) Policy determinants of business R&D;

(ii) Policy determinants of the number of new patents;

(iii) Links between innovation activities and multifactorproductivity (MFP).


Variables

Innovation policies:

R&D tax incentives: expenditure-based (R&D tax credits, taxallowances, payroll withholding tax credits for R&D wages) orincome-based (preferential tax rates for income derived fromknowledge capital)

I Measure: B-index = required rate of pre-tax return to justify $1 ofR&D outlay (tax incentive " ) B-index #)

Direct government funding of private R&D: grants, loans, loanguarantees

I Measure: ratio of government funding of private R&D to GDP

Important: stability/predictability of tax incentives and/or direct funding;two measures: # of reversals, st.dev. of B-index (not correlated in thesample)


Variables

Innovation policies:

Public R&DI Can either promote or displace private R&DI Lags can be long and di¢ cult to identify (e.g., public investment in theinternet in the 1960s)

Patent protectionI Measure: Ginarte-Park index of patent protection

Competition policies

Employment protection legislation

Trade policies

Financial and bankruptcy policies

Important: complementarity among various policies.


Data sources

OECDI Main Science and Technology Indicators Database;I Science, Technology and R&D Statistics Database;I Science Technology and Industry Outlook;I Key Economic Indicators Database;I National Accounts Database;I Employment and Labour Market Statstics

IMFI Direction of Treade Statistics

WBI Bank Regulation and Supervision Database;I Doing Business Project


Empirical models

Three empirical models (all include country- and year-FE; s.e. areclustered at country-level):1. R&D model (ECM)

∆ lnRDSit = α1∆ lnRDSit�1 + α2∆ lnBXit +m

∑j=1

ρjZjit

+θ

"lnRDSi ,t�1Yi ,t�1

� β lneri ,t�1 � n

∑j=m+1

ρjZjit

#+ ϕi + ψt + uit

RDS = annual R&D expenditure (�ow) or accumulated R&D stock. Here,erit = BXit � (rit + δ) is the real R&D-user cost (rit = long-term realinterest rate; δ = 0.15 = depreciation rate for R&D capital; Z includes mshort-run e¤ect variables (in�ation, GDP growth, etc.) and n�m long-rune¤ect variables (R&D �scal incentives, EPL, etc.).


Empirical models

2. Patenting model (ECM):

∆ lnPatitPopit

= α1∆ lnPati ,t�1Popi ,t�1

+m

∑j=1

ρjZjit

+θ

"lnPatitPopit

� β lnRDSi ,t�1Yi ,t�1

� γ ln

1+

RDSGi ,t�1RDSi ,t�1

!�

n

∑j=m+1

ρjZjit

#+ϕi + ψt + uit

Here Pop is working-age (16-64) population, RDSG is the stock of publicR&D, Z are short-run and long-run determinants.


Empirical models

3. MFP model:

∆ lnMFPit = α1∆ lnMFPLt + α2∆ lnMFPi .t�1MFPL,t�1

+n

∑j=1

ρjZjit + ϕi + eψt + uitHere MFPLt is the productivity in the frontier country, and eψt are 5-yearperiod dummies


Determinants of business R&D


Determinants of patents per worker


E¤ect of knowledge �ows on growth


Innovation policies and growth

The e¤ect of innovation policies on growth (columns 15�17) is notstatistically signi�cant. Possible reasons:

Indirect e¤ect: more sensitive to measurement error;

R&D or patent types encouraged by these policies do not increaseproductivity:

I Fiscal incentives encourage marginal projects/patents;I Information asymmetries between government and private sector;

Unintended detrimental impact: protection of incumbents deters moreproductive potential entrants;

Opportunity cost of foregone more productive projects.


ces lecture 2 nigar hashimzade · 2019-12-30 · growth with public policies in r&d ces lecture...

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